Cost and Latency Tradeoff in Mobile Edge Computing: A Distributed Game Approach

Chit Wutyee Zaw; Nway Nway Ei; Han Yeo Reum Im; Yan Kyaw Tun; Choong Seon Hong

doi:10.1109/BIGCOMP.2019.8679304

Cost and Latency Tradeoff in Mobile Edge Computing: A Distributed Game Approach

Chit Wutyee Zaw, Nway Nway Ei, Han Yeo Reum Im, Yan Kyaw Tun, Choong Seon Hong

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Citations (Scopus)

Abstract

Resource allocation has been a critical issue in Mobile Edge Computing (MEC) since MEC servers colocated at Base Stations (BS) are limited in resources and users are competitive in nature. Users' devices have restraint on power and computation capability. Moreover, users want to offload their tasks to meet their latency deadlines and they have cost for offloading their tasks. In this paper, we analyze this tradeoff between cost and latency for offloading tasks. Basically, if users want to have less latency, they need more resources to accomplish this. But, more resources to allocate to users means they have to pay more cost. In addition, we formulate the resource allocation as Generalized Nash Equilibrium Problem because users' strategies are conflicted with one another when they compete for the resources from the resources pool at the BS. We propose a distributed algorithm for the game formulation since users prefer to control their own resources rather than revealing their information to others. Then, we analyze the Price of Anarchy numerically.

Original language	English
Title of host publication	2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538677896
DOIs	https://doi.org/10.1109/BIGCOMP.2019.8679304
Publication status	Published - 1 Apr 2019
Event	2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Kyoto, Japan Duration: 27 Feb 2019 → 2 Mar 2019

Publication series

Name	2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings

Conference

Conference	2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019
Country/Territory	Japan
City	Kyoto
Period	27/02/19 → 2/03/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

Distributed Algorithm
Generalized Nash Equilibrium Problem
Mobile Edge Computing
Resource Allocation

Access to Document

10.1109/BIGCOMP.2019.8679304

Cite this

Zaw, C. W., Ei, N. N., Reum Im, H. Y., Tun, Y. K., & Hong, C. S. (2019). Cost and Latency Tradeoff in Mobile Edge Computing: A Distributed Game Approach. In 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings Article 8679304 (2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIGCOMP.2019.8679304

Zaw, Chit Wutyee ; Ei, Nway Nway ; Reum Im, Han Yeo et al. / Cost and Latency Tradeoff in Mobile Edge Computing : A Distributed Game Approach. 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings).

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title = "Cost and Latency Tradeoff in Mobile Edge Computing: A Distributed Game Approach",

abstract = "Resource allocation has been a critical issue in Mobile Edge Computing (MEC) since MEC servers colocated at Base Stations (BS) are limited in resources and users are competitive in nature. Users' devices have restraint on power and computation capability. Moreover, users want to offload their tasks to meet their latency deadlines and they have cost for offloading their tasks. In this paper, we analyze this tradeoff between cost and latency for offloading tasks. Basically, if users want to have less latency, they need more resources to accomplish this. But, more resources to allocate to users means they have to pay more cost. In addition, we formulate the resource allocation as Generalized Nash Equilibrium Problem because users' strategies are conflicted with one another when they compete for the resources from the resources pool at the BS. We propose a distributed algorithm for the game formulation since users prefer to control their own resources rather than revealing their information to others. Then, we analyze the Price of Anarchy numerically.",

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doi = "10.1109/BIGCOMP.2019.8679304",

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Zaw, CW, Ei, NN, Reum Im, HY, Tun, YK & Hong, CS 2019, Cost and Latency Tradeoff in Mobile Edge Computing: A Distributed Game Approach. in 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings., 8679304, 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019, Kyoto, Japan, 27/02/19. https://doi.org/10.1109/BIGCOMP.2019.8679304

Cost and Latency Tradeoff in Mobile Edge Computing: A Distributed Game Approach. / Zaw, Chit Wutyee; Ei, Nway Nway; Reum Im, Han Yeo et al.
2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8679304 (2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Resource allocation has been a critical issue in Mobile Edge Computing (MEC) since MEC servers colocated at Base Stations (BS) are limited in resources and users are competitive in nature. Users' devices have restraint on power and computation capability. Moreover, users want to offload their tasks to meet their latency deadlines and they have cost for offloading their tasks. In this paper, we analyze this tradeoff between cost and latency for offloading tasks. Basically, if users want to have less latency, they need more resources to accomplish this. But, more resources to allocate to users means they have to pay more cost. In addition, we formulate the resource allocation as Generalized Nash Equilibrium Problem because users' strategies are conflicted with one another when they compete for the resources from the resources pool at the BS. We propose a distributed algorithm for the game formulation since users prefer to control their own resources rather than revealing their information to others. Then, we analyze the Price of Anarchy numerically.

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Zaw CW, Ei NN, Reum Im HY, Tun YK, Hong CS. Cost and Latency Tradeoff in Mobile Edge Computing: A Distributed Game Approach. In 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8679304. (2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings). doi: 10.1109/BIGCOMP.2019.8679304

Cost and Latency Tradeoff in Mobile Edge Computing: A Distributed Game Approach

Abstract

Publication series

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Bibliographical note

Keywords

Access to Document

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